Lead the development of machine learning algorithms focusing on perception for autonomous driving, collaborating across teams and mentoring ML developers.
Our Perception team is responsible for using our sensor data to understand the complex and dynamic environments where we drive. In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components.
As a Principal ML Engineer, you will lead the development of machine learning algorithms that can range in influence from onboard autonomy to offboard autonomy and validation. You will collaborate closely with other teams specializing in Prediction, Planning, Simulation, and Safety Validation, influencing our overall technical stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. The impact of the role can be in the form of impacting immediate company milestones to leading forward-looking exploratory projects.
Responsibilities
- Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time
- Build multi-modal foundation models for on-vehicle and offline applications
- Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems
- Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
- Provide technical mentorship to the broader group of ML developers at Zoox
- Collaborate with engineers on Prediction, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments
Qualifications
- BS, MS, or PhD degree in computer science or related field
- Experience with training and deploying Deep Learning models on sensor data-Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
- Experience with modern computer vision techniques
- Strong mathematical skills and understanding of probabilistic techniques
- Fluency in C++ or Fluency in Python with a basic understanding of C++
- Extensive experience with programming and algorithm design-Strong mathematics skills
Bonus Qualifications
- Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
- Experience with autonomous robots
- Experience with realtime sensor fusion (e.g. LiDAR, camera, radar)
- Experience with novel pipelines and architectures for convolutional neural nets
- Experience with 3D data and representations (pointclouds, meshes, etc.)
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
Top Skills
C++
Deep Learning
Machine Learning
Python
Zoox Foster City, California, USA Office
4000 E 3rd Ave, Foster City, CA, United States, 94404
Zoox Foster City, California, USA Office
1149 Chess Drive, Foster City, CA, United States, 94404
Zoox Fremont, California, USA Office
47540 Kato Road, Fremont, CA, United States, 94538
Zoox San Francisco, California, USA Office
60 Broadway St, San Francisco, CA, United States, 94111
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